Leveraging Digital Technology and Artificial Intelligence to Describe the Real-World Belgian Chronic Lymphocytic Leukemia Patient Population: The BE-CLLEAR Study

This AI-augmented study demonstrates the feasibility and scalability of combining NLP-derived insights with OMOP-standardized structured data to generate reproducible RWE in hematology. Our results highlight an elderly CLL population with significant comorbidities and a shift toward targeted therapies. While treatment patterns aligned with guidelines, data quality depended on source documentation accessibility. Improved integration of molecular testing into electronic health records is essential for enhancing clinical decision making, patient outcomes, and future research.